Traffic Analytics

Traffic Analytics gives you direct access to your GA4 data through BigQuery, enabling powerful custom analyses beyond pre-built reports.

Prerequisites

Before using Traffic Analytics, you need:

1. BigQuery Integration - Connect your GA4 BigQuery export
2. GA4 Tracking - Have Google Analytics tracking your app listing

If you haven't set this up yet, see Connect BigQuery.

Accessing Traffic Analytics

1. Go to My Apps and select your app
2. Click Traffic in the sidebar navigation
3. The SQL query interface will load with your BigQuery data

What You Can Do

Write Custom SQL Queries

The SQL editor supports:

• Full BigQuery Standard SQL syntax
• Syntax highlighting for readability
• Query validation before execution
• Configurable result limits
• Export results to CSV

Pre-built Query Templates

Get started faster with templates for common analyses:

User Journey Analysis

• Track complete paths from discovery to conversion
• Identify drop-off points
• Understand multi-touch attribution

Conversion Attribution

• First-touch and last-touch attribution
• Multi-touch attribution models
• Channel contribution analysis

Session Analysis

• Session duration patterns
• Pages per session
• Bounce rate analysis
• Engagement metrics

Event Stream Queries

• Event sequences and funnels
• Cohort analysis
• Retention queries

Using a Template

1. Select a template from the library
2. Customize parameters (dates, filters)
3. Review the SQL query
4. Click Run Query
5. Save your customized version for future use

Understanding Your Data

Available Data

Your BigQuery export includes:

• Pageviews - App listing page visits
• Clicks - Button and link clicks
• Form Submissions - Trial starts, signups
• Purchases - Install completions
• Custom Events - App-specific tracking

Common Fields

Best Practices

Query Optimization Tips

Do:

• Start with small date ranges to test queries
• Use specific columns instead of SELECT *
• Filter by date partitions
• Use LIMIT while testing
• Check query cost estimation before running

Avoid:

• Querying entire datasets without filters
• Full table scans
• Nested subqueries when unnecessary
• Running expensive queries repeatedly

Cost Management

BigQuery pricing:

• First 1 TB/month is free
• $5 per TB after that
• Typical monthly cost: $5-20

The query cost is shown before execution so you can avoid surprises.

Common Use Cases

Find Your Best Traffic Sources

Identify which sources drive the most conversions:

SELECT
  traffic_source.source,
  COUNT(*) as sessions,
  COUNTIF(event_name = 'install') as installs
FROM `your_table`
WHERE event_date BETWEEN 'YYYY-MM-DD' AND 'YYYY-MM-DD'
GROUP BY 1
ORDER BY installs DESC

Analyze User Paths

See how users navigate to installation:

-- Track the sequence of events leading to install
SELECT user_pseudo_id, event_name, event_timestamp
FROM `your_table`
WHERE user_pseudo_id IN (
  SELECT DISTINCT user_pseudo_id
  FROM `your_table`
  WHERE event_name = 'install'
)
ORDER BY user_pseudo_id, event_timestamp

Geographic Performance

Compare conversion rates by country:

SELECT
  geo.country,
  COUNT(DISTINCT user_pseudo_id) as users,
  COUNTIF(event_name = 'install') as installs,
  SAFE_DIVIDE(COUNTIF(event_name = 'install'), COUNT(DISTINCT user_pseudo_id)) as conversion_rate
FROM `your_table`
GROUP BY 1
ORDER BY installs DESC
LIMIT 20

Saving Queries

Save frequently used queries for quick access:

1. Write or modify a query
2. Click Save Query
3. Give it a descriptive name
4. Access saved queries from your library

Troubleshooting

"Permission Denied" Error

• Verify your BigQuery connection in Settings
• Check that OAuth permissions are still valid
• Try re-authorizing your Google account

"Query Timeout" Error

• Reduce your date range
• Add more filters to limit data
• Simplify complex queries
• Try sampling larger datasets

No Results Returned

• Check that your date range has data
• Verify event names match exactly
• Confirm filters aren't too restrictive
• Check if data has synced for that period

Query Cost Too High

• Add date filters to limit data scanned
• Use specific columns instead of SELECT *
• Consider aggregating data first
• Use query dry-run to estimate costs

FAQ

Q: How real-time is the data? A: GA4 exports to BigQuery daily. For same-day data, check the events_intraday_* tables.

Q: Can I connect multiple BigQuery projects? A: Currently, one BigQuery connection per app. Contact support for enterprise options.

Q: Why is my query slow? A: Large date ranges and full table scans are the most common causes. Always filter by date first.

Q: Can I schedule recurring queries? A: Not currently in Ranksy. Use BigQuery scheduled queries directly for automated reports.

Need help with SQL? Check out BigQuery SQL Reference or contact [email protected].